Exemplary embodiments of the present invention relate to an apparatus and method for the learning emotion of a robot, and more particularly, to an apparatus for the learning emotion of a robot and a method for the learning emotion of a robot, which are capable of generating emotions desired by a user through learning.
In general, the emotions of a robot are limited to emotions that are generated in specific positions of an emotion space having a specific number of emotions according to inputs through sensors.
FIG. 1 is a schematic diagram showing a common emotional expression method of a robot.
In order for a robot to express emotions, current emotion values of the robot have to be calculated. Emotion is rarely determined to be one detailed emotion, such as happiness or sadness. Although a human being now feels happy, different emotions, such as surprise and anger, are partially incorporated. That is, an emotional expression is a result into which complex detailed emotions are incorporated. Accordingly, in order to embody a realistic emotional expression through a robot, emotion values applied to the robot can also be expressed by vectors by incorporating a variety of detailed emotions, such as happiness, sadness, surprise, and anger.
In general, in order to express the emotions of a robot as in FIG. 1, a two-dimensional or three-dimensional fixed space is used. An emotion and an emotional expression corresponding to the emotion are mapped to a specific position on the space of the fixed dimension. An emotion value can be represented and calculated as a vector value corresponding to the specific position on the space.
That is, a method of mapping emotions to several points on a vector space, mapping emotional expressions to respective corresponding emotions, selecting one of the emotions that is closest to a specific emotion vector from the several emotions mapped to the vector space when the specific emotion vector is given, and making an emotional expression mapped to the selected emotion has been used.
In other words, the manual mapping of emotions and emotional expression, corresponding to the emotions, to numerous coordinates on the vector space is limited. Thus, in the method of FIG. 1, a small number of coordinates are selected, the emotions corresponding to the respective coordinates are mapped to emotional expression behaviors corresponding to the emotions, an emotion having coordinates that are closest to an emotion vector determined by considering the emotion state of a robot is selected, and a corresponding emotional expression is performed.
For example, if emotion values 1 {happiness 1, sadness 0, surprise 0, anger 0) are set so that it is shown in coordinates 1 on a four-dimensional vector space and emotion values 2 {happiness ¾, sadness ¼, surprise 0, anger 0} and emotion values 3 {happiness ¾, sadness 0, surprise ¼, surprise 0} are closer to the coordinates 1 than to coordinates that represent different emotions, all the emotion values 1, 2, and 3 perform the emotional expressions set in the coordinates 1.
As described above, in the conventional method, even when emotion values internally generated actually are different from each other, only the most similar one emotion value is selected from emotion values corresponding to the coordinates 1 and an emotional expression behavior is selected based on the emotion value of the same coordinates. Accordingly, forms that are represented through an expression organ are the same.
A detailed description is given with reference to FIG. 2. FIG. 2 is a schematic diagram illustrating a conventional process of generating the emotions of a robot from emotion state input values. In FIG. 2, a one-dimensional emotion coordinate system is used, for convenience of description.
In the emotion coordinate system, it is assumed that a basic emotion of happiness is disposed at coordinates 1 and a basic emotion of sadness is disposed at coordinates −1. If an input value is 0.3, a basic emotion that is closest to 0.3 is extracted. In the case of FIG. 2, the basic emotion of happiness is extracted because 0.3 is closer to 1 than to −1. The final emotion of a robot becomes the coordinates 1 because the basic emotion of happiness becomes the coordinates 1 in the emotion coordinate system.
In accordance with the emotion generation method, although an input value is 0.5, the final emotion of the robot will become the coordinates 1 as in a case where the input value is 0.3.
Accordingly, from a viewpoint of an emotional expression apparatus for expressing an eye, a mouth, and a gesture based on the emotions of a robot that are generated in accordance with the emotion generation method, the same coordinates 1 are expressed by an emotion of a robot even when an emotion state input value is 0.3 and 0.5. Accordingly, in most of robots, the emotional expression is made although an input value is different.
However, the conventional robot emotion generation apparatus generates always the same emotion for the same input. If an unwanted emotion is produced according to a user's propensity, there are problems in that the user does not sympathize with the robot and an interest in the robot is reduced by half.